2022. December 5.
‘Tragedy of the commons’: limited incentives for any single actor to stop overusing1…
Global common resources, such as air, water, fisheries have been overused and polluted for the past decades
Mismatched costs and benefits: resource users do not bear the costs of pollution or overuse directly, or immediately
Traditional solutions, especially local ones, cannot effectively limit global warning as cross-country resources are affected
International cooperation on climate change is necessary to limit its effects
…but international solutions so far have been lacking in providing effective solutions
Multiple times, global or regional solutions have been attempted to limit pollution and curtail global warning
But with limited enforcement power, these solutions so far have not achieved a significant reduction in greenhouse gas emissions2
The latest climate agreements, known as the Paris Agreement and the newly decided ‘Damage and Loss’ initiative at COP27 try to provide a framework to reduce emissions and mitigate existing consequences3
Figure 1: Illustrative example of literature
Studies typically show people are concerned about climate change (e.g., ~60%+ of Americans are somewhat concerned4), that younger generations are more concerned5, or that income, education or political views matter6
Yet how different perspectives potentially influence each other is less commonly explored
People’s views and opinions on climate action or the results of those actions might be influenced by, or correlated with other views they hold about the world - for example, how they think about diversity, their own country, or democracy in general
Question 1: Is people’s satisfaction with democracy in their own country or their views on diversity influences how they perceive international climate action?
Y: People’s belief if international climate actions can solve climate change
X1: People’s satisfaction with democracy in their own country, understood as a binary indicator (satisfied / not satisfied)
X2: People’s opinion on whether diversity makes the world a better place (i.e., having people with different backgrounds, such as different ethnic groups, religions and races living in their country is good or bad)
Control variables: age, gender, income, education, climate concern, race
Question 2: Does this relationship differ across countries in the developed world?
Hypothesis: We expect a significant positive relationship for both independent variables across countires
Measurement: Top10 global polluters7
United States
Germany
South Korea
Measurement: per capita fossil fuel usage has been decreasing 8
Australia
Sweden
The Netherlands
1. Global Attitudes Survey, Spring 2021, Pew Research Center
2. American Trends Panel, February 2021, Pew Research Center
 1. Subset only to countries that relate to the scope of our analysis
 2. To allow for comparability across countries:
Cleaning data within the focal country of analysis
Cleaning data across countries
Cleaning within the Global dataset (but across AU, DE, NL, KR, SE)
Figure 2: Illustrative example of three countries, raw values
Figure 3: Illustrative example of three countries, initial recoding
Figure 4: Illustrative example of three countries, final recoded version
Figure 5: Illustrative example of four countries, raw values
Figure 5: Illustrative example of four countries, final recoded version
Thus, recode:
 3. To perform a logistic regression, create a binary variable for the Y variable (CLIMATE_CONFIDENCE)
 4. Convert ‘Don’t Know’ and ‘Refused’ to NAs
 5. Change the order of the columns so that we can identify the respondents’ nationality at first glance. Then, select only the variables relevant to our analysis.
 6. Merge the Global dataset and the US dataset
Defining our hypothesized multiple logistic regression models
Consolidating and interpreting the coefficient estimates of the regression tables and their statistical significance
Figure 6: regression results across the six country models
Figure 8: Predicted probabilities, democracy perceptions
(provided that control variables are set to their median levels)
Note: Small differences in the predicted probabilities for the two groups in Korea is consistent with our findings that the effect of satisfaction with democracy was significant (at 0.1 significance level, as opposed to the conventional 0.05 level) using the p-value approach, and that we failed to reject the null hypothesis using the CI approach - by an extremely narrow margin
Figure 8: Predicted probabilities, diversity
 1. The difficulty of getting the world’s largest powers involved in combating climate change and set an example for the others, despite the importance of collective effort.
 2. The belief that international efforts to take climate action such as the COP26 are more of an “empty talk” and “empty promises”
Figure 8: Predicted probabilities, diversity
Korea’s increased presence in the multilateral stage and the pledge of “action and solidarity” at the COP26, APEC, and G20 summit, where the climate crisis was high on the agenda
| Dependent variable: | ||||||
| CLIMATE_CONFIDENCE | ||||||
| AUSTRALIA | KOREA | GERMANY | NETHERLANDS | SWEDEN | USA | |
| (1) | (2) | (3) | (4) | (5) | (6) | |
| DIVERSITY_GOOD | 0.344 | 0.416** | 0.463** | 0.424*** | 0.560*** | 0.568*** |
| (0.246) | (0.163) | (0.186) | (0.162) | (0.198) | (0.188) | |
| SATISFIED_DEMOCRACY | -0.288*** | -0.184* | -0.393*** | -0.655*** | -0.438*** | -0.720*** |
| (0.090) | (0.097) | (0.079) | (0.087) | (0.098) | (0.064) | |
| CLIMATE_CONCERN | -0.410*** | -0.472*** | -0.082 | -0.172** | -0.128 | -0.795*** |
| (0.083) | (0.107) | (0.079) | (0.084) | (0.081) | (0.059) | |
| FEMALE | 0.308** | 0.305* | 0.181 | 0.097 | -0.141 | 0.288*** |
| (0.151) | (0.182) | (0.150) | (0.151) | (0.144) | (0.099) | |
| AGECAT | -0.021 | 0.113 | 0.230*** | 0.123* | -0.086 | -0.056 |
| (0.076) | (0.091) | (0.074) | (0.071) | (0.072) | (0.050) | |
| EDUCATION | -0.355** | 0.156 | -0.184 | -0.625*** | -0.134 | -0.095 |
| (0.162) | (0.169) | (0.163) | (0.163) | (0.157) | (0.108) | |
| POLITICAL_ID | -0.074 | -0.083 | 0.128 | 0.170* | 0.081 | -0.346*** |
| (0.110) | (0.117) | (0.104) | (0.098) | (0.095) | (0.073) | |
| INCOME | 0.059 | 0.055 | -0.406*** | -0.050 | -0.481*** | -0.047 |
| (0.166) | (0.173) | (0.155) | (0.165) | (0.151) | (0.107) | |
| Constant | 1.236** | 1.588*** | 0.225 | 1.483*** | 0.611 | 3.770*** |
| (0.511) | (0.464) | (0.432) | (0.441) | (0.449) | (0.335) | |
| Observations | 782 | 807 | 834 | 860 | 960 | 2,382 |
| Log Likelihood | -512.243 | -472.542 | -541.840 | -538.488 | -605.132 | -1,273.024 |
| Akaike Inf. Crit. | 1,042.486 | 963.084 | 1,101.679 | 1,094.975 | 1,228.264 | 2,564.047 |
| Note: | ***: p < 0.01; **: p < 0.05; *: p < 0.1 | |||||
1: https://online.hbs.edu/blog/post/tragedy-of-the-commons-impact-on-sustainability-issues
2: https://www.un.org/en/climatechange/cop27
3: https://www.un.org/en/climatechange/cop27
7: https://climatetrade.com/which-countries-are-the-worlds-biggest-carbon-polluters/
8: https://ourworldindata.org/grapher/annual-change-fossil-fuels?tab=table
Age
Income
Political affiliation
Political affiliation
Education
Gender